Landslide susceptibility modelling using the quantitative random forest method along the northern portion of the Yukon Alaska Highway Corridor, Canada

Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia

(2015) Ahmed Mohamed Youssef et al.   Landslides

Data- and knowledge-driven mineral prospectivity maps for Canada's North

(2015) J.R. Harris et al.   ORE GEOLOGY REVIEWS

Comparison of the Data-Driven Random Forests Model and a Knowledge-Driven Method for Mineral Prospectivity Mapping: A Case Study for Gold Deposits Around the Huritz Group and Nueltin Suite, Nunavut, Canada

(2015) G. McKay et al.   Natural Resources Research

Debris Flow Chronology and Potential Hazard along the Alaska Highway in Southwest Yukon Territory

(2014) J. KOCH et al.   ENVIRONMENTAL & ENGINEERING GEOSCIENCE

Predictive modelling of gold potential with the integration of multisource information based on random forest: a case study on the Rodalquilar area, Southern Spain

(2014) V.F. Rodriguez-Galiano et al.   INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

Machine Learning Feature Selection Methods for Landslide Susceptibility Mapping

(2013) Natan Micheletti et al.   Mathematical Geosciences

imageRF – A user-oriented implementation for remote sensing image analysis with Random Forests

(2012) Björn Waske et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Learning from Imbalanced Data

(2009) Haibo He et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING